Volume 9 Supplement 1

VII Madrid Breast Cancer Conference: Changes in the treatment of breast cancer

Open Access

Molecular and gene expression-based predictors of response to preoperative chemotherapy

  • L Pusztai1
Breast Cancer Research20079(Suppl 1):S5

https://doi.org/10.1186/bcr1688

Received: 23 May 2007

Published: 19 June 2007

Many single-gene molecular markers have been evaluated as predictors of response to specific regimens. However, no reliable and routinely used molecular chemotherapy response predictors exist today. Molecular markers of proliferative activity remain nonspecific predictors of chemotherapy sensitivity in general. Multidrug-resistance transport proteins, p53 gene mutations, and defects in apoptotic pathways remain highly controversial as predictors of response or resistance to particular drugs. To date, the strongest (although still indirect) evidence supporting a molecular predictor of response to a particular regimen comes from a retrospective subset analysis of a variety of studies that showed a link between topoisomerase II amplification and increased sensitivity to anthracyclines. However, the best methodology for determining amplification of topoisomerase II and the appropriate cut-off value to distinguish between individuals with and without amplification have not been established.

Several small studies provided 'proof-of-principle' that the gene expression profile of cancers that are highly sensitive to chemotherapy is different from that of tumors resistant to treatment. Table 1 presents a summary of the current literature. The most exciting possibility implicit to gene expression profiling-based diagnostic tests is that multiple predictors could be applied to a single data set. It is currently technically feasible to perform gene expression profiling on a single biopsy and assess prognosis using a 76-gene, or 70-gene signature, determine the ER and HER-2 status by measuring receptor mRNA levels, predict endocrine sensitivity among the ER-positive patients and estimate the probability of response chemotherapy.

Table 1

Reference

Patient characteristics

Treatment

Results

Chang et al. [1]

24 (discovery) and 6 (validation) patients. with LABC

4 cycles docetaxel every 3 weeks

92 differentially expressed genes (P < 0.001) LOOCV results in training: predictive accuracy of 88% (95% CI, 68–97%), PPV of 92%, NPV of 83%, sensitivity of 85% (95% CI, 55–98%), specificity of 91% (95% CI, 59–100%)

   

Independent validation: all six patients with sensitive tumors correctly identified

Ayers et al. [2]

24 (discovery) and 12 (validation) patients with breast cancer

3 or 12 cycles paclitaxel and 4 cycles of FAC (T/FAC)

No single gene sufficiently associated with pCR to serve as single valid marker 74-gene predictor for response to chemotherapy

   

- Predictive accuracy of 78% (95% CI, 52–94%), PPV of 100% (95% CI, 29–100%), NPV of 73% (95% CI, 45–92%), sensitivity of 43% (95% CI, 10–82%), specificity of 100% (95% CI, 72–100%)

Iwao-Koizumi et al. [3]

44 (discovery) and 26 (validation) patients. with stage II/IV breast cancer

4 cycles of docetaxel

85-gene-predictor of pCR with:

   

- Predictive accuracy of 80.7% (95% CI, 63.5–92.5%), PPV of 73.3% (95% CI, 49.5–90.3%), NPV of 90.9% (95% CI, 65.9–99.4%), sensitivity of 91.7% (95% CI, 68.1–99.5%), specificity of 71.4% (95% CI, 46.7–89.5%)

Hannemann et al. [4]

48 patients with LABC

6 cycles of doxorubicin/docetaxel (AD, n = 24) or doxorubicin/cyclophosphamide (AC, n = 24)

No differentially expressed genes identified, no possible multigene predictor developed

   

Patient samples did not cluster distinctly for pCR/near pCR compared with RD in hierarchical clustering

Gianni et al. [5]

89 (INT-Milan) and 82 (MDACC) patients with LABC

3 cycles of doxorubicin/paclitaxel, 12 cycles of weekly paclitaxel

86 genes correlating with pCR (P < 0.05) forming three clusters

   

- ER gene cluster

   

- Proliferation gene cluster

   

- Immune-related gene cluster

   

RS correlated with pCR in INT-Milan patients 86-gene model developed on INT-Milan patients validated on MDACC samples

Folgueira et al. [6]

(1) 38 (discovery), 13 (validation)

 

(1) 25 (3.8%) differentially expressed transcripts between responders and non-responders, three-gene classifier could not be validated

 

(2) 31 (discovery), 13 (validation)

 

(2) Three-gene classifier successfully developed and validated both by LOOCV and in an independent validation set

Dressman et al. [7]

37 patients with stage IIB/III breast cancer

Liposomal doxorubicin × 4/paclitaxel combined with local whole breast hyperthermia

(a) 22-gene signature characterizing IBC identified and validated by LOOVC

   

(b) 18-gene signature characterizing IBC identified and validated by LOOVC

   

(c) No gene signature predicting clinical response could be identified

Thuerigen et al. [8]

52 (discovery/GEsDoc), 48 (validation/GEDoc) patients with T2-4N0-2M0 breast cancer

GEsDoc (gemcitabine, epirubicin every 2 weeks × 5 followed by docetaxel every 2 weeks × 2), GEDoc (gemcitabine, epirubicin, docetaxel every 3 weeks)

512-gene-signature predictive of pCR: predictive accuracy of 88% (95% CI, 75–95%), PPV of 64% (95% CI, 39–81%), NPV of 95% (95% CI, 82–99%), sensitivity of 78% (95% CI, 40–97%), specificity of 90% (95% CI, 76–97%)

Park et al. [9]

21 patients with stage II/III breast cancer

4 cycles of FEC every 3 weeks followed by 12 cycles of weekly paclitaxel

11 differentially expressed ABC transporters Multigene predictor model with the ABC transporters differentially expressed between the two classes (P < 0.003) with predictive of pCR with:

   

- Predictive accuracy of 92.8% (95% CI, 88.0–97.4%), PPV of 93.2% (95% CI, 85.2–100%), NPV of 93.6% (95% CI, 87.8–99.4%), sensitivity of 88.1% (95% CI, 76.8–99.4%), specificity of 95.9% (95% CI, 87.8–100%)

Cleator et al. [10]

40 patients with primary breast cancer

6 cycles doxorubicin/cyclophosphamide (AC)

253 differentially expressed genes;

   

- 75 genes overexpressed in resistant tumors (that is, transcription, differentiation, signal transduction, amino acid metabolism)

   

- 178 genes overexpressed in sensitive tumors (that is, cell cycle, survival, stress response, and estrogen-regulated genes)

Hess et al. [11]

82 (discovery), 51 (validation)

3 or 12 cycles paclitaxel and 4 cycles of FAC (T/FAC)

30-gene predictor identified and validated by fivefold cross-validation, permutation testing and application to an independent data set:

   

- Predictive accuracy of 76% (95% CI, 62–87%), PPV of 52% (95% CI, 31–73%), NPV of 96% (95% CI, 82–100%), sensitivity of 92% (95% CI, 64–100%), specificity of 71% (95% CI, 54–85%)

Mina et al. [12]

45 patients with stage II/III breast cancer

3 cycles doxorubicin every 2 weeks and 6 cycles docetaxel weekly × 6

22 of 274 candidate genes correlated with pCR (P < 0.05) forming three large clusters: angiogenesis-related genes, proliferation-related genes, invasion-related genes, no correlation between RS and pCR, 24/274 genes correlated with inflammatory phenotype

ABC transporter, ATP binding cassette transporter; discovery, development/training set; FAC, 5-fluorouracil, doxorubicine, cyclophosphamide; FEC, 5-fluorouracil, epirubicin, cyclophosphamide; IBC, inflammatory breast cancer; LABC, locally advanced breast cancer; LOOCV, leave-one-out cross-validation; NPV, negative predictive value; pCR, pathological complete response; PPV, positive predictive value; RD, residual disease; RS, recurrence score (Oncotype DX©); validation, validation set.

Authors’ Affiliations

(1)
The University of Texas MD Anderson Cancer Center

References

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© BioMed Central Ltd 2007

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